InvokeAI/ldm/invoke/readline.py

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"""
Readline helper functions for invoke.py.
You may import the global singleton `completer` to get access to the
completer object itself. This is useful when you want to autocomplete
seeds:
from ldm.invoke.readline import completer
completer.add_seed(18247566)
completer.add_seed(9281839)
"""
import os
import re
import atexit
from ldm.invoke.args import Args
# ---------------readline utilities---------------------
try:
import readline
readline_available = True
except (ImportError,ModuleNotFoundError):
readline_available = False
IMG_EXTENSIONS = ('.png','.jpg','.jpeg','.PNG','.JPG','.JPEG','.gif','.GIF')
add ability to import and edit alternative models online - !import_model <path/to/model/weights> will import a new model, prompt the user for its name and description, write it to the models.yaml file, and load it. - !edit_model <model_name> will bring up a previously-defined model and prompt the user to edit its descriptive fields. Example of !import_model <pre> invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b> >> Model import in process. Please enter the values needed to configure this model: Name for this model: <b>waifu-diffusion</b> Description of this model: <b>Waifu Diffusion v1.3</b> Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b> Default image width: <b>512</b> Default image height: <b>512</b> >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? <b>y</b> >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt | LatentDiffusion: Running in eps-prediction mode | DiffusionWrapper has 859.52 M params. | Making attention of type 'vanilla' with 512 in_channels | Working with z of shape (1, 4, 32, 32) = 4096 dimensions. | Making attention of type 'vanilla' with 512 in_channels | Using faster float16 precision </pre> Example of !edit_model <pre> invoke> <b>!edit_model waifu-diffusion</b> >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: <b>Waifu diffusion v1.4beta</b> weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b> config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ... </pre>
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WEIGHT_EXTENSIONS = ('.ckpt','.bae')
CONFIG_EXTENSIONS = ('.yaml','.yml')
COMMANDS = (
'--steps','-s',
'--seed','-S',
'--iterations','-n',
'--width','-W','--height','-H',
'--cfg_scale','-C',
'--threshold',
'--perlin',
'--grid','-g',
'--individual','-i',
'--save_intermediates',
'--init_img','-I',
'--init_mask','-M',
'--init_color',
'--strength','-f',
'--variants','-v',
'--outdir','-o',
'--sampler','-A','-m',
'--embedding_path',
'--device',
'--grid','-g',
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'--facetool','-ft',
'--facetool_strength','-G',
'--codeformer_fidelity','-cf',
'--upscale','-U',
'-save_orig','--save_original',
'--skip_normalize','-x',
'--log_tokenization','-t',
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'--hires_fix',
'--inpaint_replace','-r',
'--png_compression','-z',
'--text_mask','-tm',
'!fix','!fetch','!replay','!history','!search','!clear',
'!mask',
add ability to import and edit alternative models online - !import_model <path/to/model/weights> will import a new model, prompt the user for its name and description, write it to the models.yaml file, and load it. - !edit_model <model_name> will bring up a previously-defined model and prompt the user to edit its descriptive fields. Example of !import_model <pre> invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b> >> Model import in process. Please enter the values needed to configure this model: Name for this model: <b>waifu-diffusion</b> Description of this model: <b>Waifu Diffusion v1.3</b> Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b> Default image width: <b>512</b> Default image height: <b>512</b> >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? <b>y</b> >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt | LatentDiffusion: Running in eps-prediction mode | DiffusionWrapper has 859.52 M params. | Making attention of type 'vanilla' with 512 in_channels | Working with z of shape (1, 4, 32, 32) = 4096 dimensions. | Making attention of type 'vanilla' with 512 in_channels | Using faster float16 precision </pre> Example of !edit_model <pre> invoke> <b>!edit_model waifu-diffusion</b> >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: <b>Waifu diffusion v1.4beta</b> weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b> config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ... </pre>
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'!models','!switch','!import_model','!edit_model'
enable fast switching between models in invoke.py - This PR enables two new commands in the invoke.py script !models -- list the available models and their cache status !switch <model> -- switch to the indicated model Example: invoke> !models laion400m not loaded Latent Diffusion LAION400M model stable-diffusion-1.4 active Stable Diffusion inference model version 1.4 waifu-1.3 cached Waifu anime model version 1.3 invoke> !switch waifu-1.3 >> Caching model stable-diffusion-1.4 in system RAM >> Retrieving model waifu-1.3 from system RAM cache The name and descriptions of the models are taken from `config/models.yaml`. A future enhancement to `model_cache.py` will be to enable new model stanzas to be added to the file programmatically. This will be useful for the WebGUI. More details: - Use fast switching algorithm described in PR #948 - Models are selected using their configuration stanza name given in models.yaml. - To avoid filling up CPU RAM with cached models, this PR implements an LRU cache that monitors available CPU RAM. - The caching code allows the minimum value of available RAM to be adjusted, but invoke.py does not currently have a command-line argument that allows you to set it. The minimum free RAM is arbitrarily set to 2 GB. - Add optional description field to configs/models.yaml Unrelated fixes: - Added ">>" to CompViz model loading messages in order to make user experience more consistent. - When generating an image greater than defaults, will only warn about possible VRAM filling the first time. - Fixed bug that was causing help message to be printed twice. This involved moving the import line for the web backend into the section where it is called. Coauthored by: @ArDiouscuros
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)
MODEL_COMMANDS = (
'!switch',
add ability to import and edit alternative models online - !import_model <path/to/model/weights> will import a new model, prompt the user for its name and description, write it to the models.yaml file, and load it. - !edit_model <model_name> will bring up a previously-defined model and prompt the user to edit its descriptive fields. Example of !import_model <pre> invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b> >> Model import in process. Please enter the values needed to configure this model: Name for this model: <b>waifu-diffusion</b> Description of this model: <b>Waifu Diffusion v1.3</b> Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b> Default image width: <b>512</b> Default image height: <b>512</b> >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? <b>y</b> >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt | LatentDiffusion: Running in eps-prediction mode | DiffusionWrapper has 859.52 M params. | Making attention of type 'vanilla' with 512 in_channels | Working with z of shape (1, 4, 32, 32) = 4096 dimensions. | Making attention of type 'vanilla' with 512 in_channels | Using faster float16 precision </pre> Example of !edit_model <pre> invoke> <b>!edit_model waifu-diffusion</b> >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: <b>Waifu diffusion v1.4beta</b> weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b> config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ... </pre>
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'!edit_model',
)
WEIGHT_COMMANDS = (
'!import_model',
)
IMG_PATH_COMMANDS = (
'--outdir[=\s]',
)
IMG_FILE_COMMANDS=(
'!fix',
'!fetch',
'!mask',
'--init_img[=\s]','-I',
'--init_mask[=\s]','-M',
'--init_color[=\s]',
'--embedding_path[=\s]',
)
add ability to import and edit alternative models online - !import_model <path/to/model/weights> will import a new model, prompt the user for its name and description, write it to the models.yaml file, and load it. - !edit_model <model_name> will bring up a previously-defined model and prompt the user to edit its descriptive fields. Example of !import_model <pre> invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b> >> Model import in process. Please enter the values needed to configure this model: Name for this model: <b>waifu-diffusion</b> Description of this model: <b>Waifu Diffusion v1.3</b> Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b> Default image width: <b>512</b> Default image height: <b>512</b> >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? <b>y</b> >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt | LatentDiffusion: Running in eps-prediction mode | DiffusionWrapper has 859.52 M params. | Making attention of type 'vanilla' with 512 in_channels | Working with z of shape (1, 4, 32, 32) = 4096 dimensions. | Making attention of type 'vanilla' with 512 in_channels | Using faster float16 precision </pre> Example of !edit_model <pre> invoke> <b>!edit_model waifu-diffusion</b> >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: <b>Waifu diffusion v1.4beta</b> weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b> config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ... </pre>
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path_regexp = '('+'|'.join(IMG_PATH_COMMANDS+IMG_FILE_COMMANDS) + ')\s*\S*$'
weight_regexp = '('+'|'.join(WEIGHT_COMMANDS) + ')\s*\S*$'
class Completer(object):
enable fast switching between models in invoke.py - This PR enables two new commands in the invoke.py script !models -- list the available models and their cache status !switch <model> -- switch to the indicated model Example: invoke> !models laion400m not loaded Latent Diffusion LAION400M model stable-diffusion-1.4 active Stable Diffusion inference model version 1.4 waifu-1.3 cached Waifu anime model version 1.3 invoke> !switch waifu-1.3 >> Caching model stable-diffusion-1.4 in system RAM >> Retrieving model waifu-1.3 from system RAM cache The name and descriptions of the models are taken from `config/models.yaml`. A future enhancement to `model_cache.py` will be to enable new model stanzas to be added to the file programmatically. This will be useful for the WebGUI. More details: - Use fast switching algorithm described in PR #948 - Models are selected using their configuration stanza name given in models.yaml. - To avoid filling up CPU RAM with cached models, this PR implements an LRU cache that monitors available CPU RAM. - The caching code allows the minimum value of available RAM to be adjusted, but invoke.py does not currently have a command-line argument that allows you to set it. The minimum free RAM is arbitrarily set to 2 GB. - Add optional description field to configs/models.yaml Unrelated fixes: - Added ">>" to CompViz model loading messages in order to make user experience more consistent. - When generating an image greater than defaults, will only warn about possible VRAM filling the first time. - Fixed bug that was causing help message to be printed twice. This involved moving the import line for the web backend into the section where it is called. Coauthored by: @ArDiouscuros
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def __init__(self, options, models=[]):
self.options = sorted(options)
enable fast switching between models in invoke.py - This PR enables two new commands in the invoke.py script !models -- list the available models and their cache status !switch <model> -- switch to the indicated model Example: invoke> !models laion400m not loaded Latent Diffusion LAION400M model stable-diffusion-1.4 active Stable Diffusion inference model version 1.4 waifu-1.3 cached Waifu anime model version 1.3 invoke> !switch waifu-1.3 >> Caching model stable-diffusion-1.4 in system RAM >> Retrieving model waifu-1.3 from system RAM cache The name and descriptions of the models are taken from `config/models.yaml`. A future enhancement to `model_cache.py` will be to enable new model stanzas to be added to the file programmatically. This will be useful for the WebGUI. More details: - Use fast switching algorithm described in PR #948 - Models are selected using their configuration stanza name given in models.yaml. - To avoid filling up CPU RAM with cached models, this PR implements an LRU cache that monitors available CPU RAM. - The caching code allows the minimum value of available RAM to be adjusted, but invoke.py does not currently have a command-line argument that allows you to set it. The minimum free RAM is arbitrarily set to 2 GB. - Add optional description field to configs/models.yaml Unrelated fixes: - Added ">>" to CompViz model loading messages in order to make user experience more consistent. - When generating an image greater than defaults, will only warn about possible VRAM filling the first time. - Fixed bug that was causing help message to be printed twice. This involved moving the import line for the web backend into the section where it is called. Coauthored by: @ArDiouscuros
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self.models = sorted(models)
self.seeds = set()
self.matches = list()
self.default_dir = None
self.linebuffer = None
self.auto_history_active = True
add ability to import and edit alternative models online - !import_model <path/to/model/weights> will import a new model, prompt the user for its name and description, write it to the models.yaml file, and load it. - !edit_model <model_name> will bring up a previously-defined model and prompt the user to edit its descriptive fields. Example of !import_model <pre> invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b> >> Model import in process. Please enter the values needed to configure this model: Name for this model: <b>waifu-diffusion</b> Description of this model: <b>Waifu Diffusion v1.3</b> Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b> Default image width: <b>512</b> Default image height: <b>512</b> >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? <b>y</b> >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt | LatentDiffusion: Running in eps-prediction mode | DiffusionWrapper has 859.52 M params. | Making attention of type 'vanilla' with 512 in_channels | Working with z of shape (1, 4, 32, 32) = 4096 dimensions. | Making attention of type 'vanilla' with 512 in_channels | Using faster float16 precision </pre> Example of !edit_model <pre> invoke> <b>!edit_model waifu-diffusion</b> >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: <b>Waifu diffusion v1.4beta</b> weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b> config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ... </pre>
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self.extensions = None
return
def complete(self, text, state):
'''
Completes invoke command line.
BUG: it doesn't correctly complete files that have spaces in the name.
'''
buffer = readline.get_line_buffer()
if state == 0:
add ability to import and edit alternative models online - !import_model <path/to/model/weights> will import a new model, prompt the user for its name and description, write it to the models.yaml file, and load it. - !edit_model <model_name> will bring up a previously-defined model and prompt the user to edit its descriptive fields. Example of !import_model <pre> invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b> >> Model import in process. Please enter the values needed to configure this model: Name for this model: <b>waifu-diffusion</b> Description of this model: <b>Waifu Diffusion v1.3</b> Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b> Default image width: <b>512</b> Default image height: <b>512</b> >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? <b>y</b> >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt | LatentDiffusion: Running in eps-prediction mode | DiffusionWrapper has 859.52 M params. | Making attention of type 'vanilla' with 512 in_channels | Working with z of shape (1, 4, 32, 32) = 4096 dimensions. | Making attention of type 'vanilla' with 512 in_channels | Using faster float16 precision </pre> Example of !edit_model <pre> invoke> <b>!edit_model waifu-diffusion</b> >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: <b>Waifu diffusion v1.4beta</b> weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b> config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ... </pre>
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# extensions defined, so go directly into path completion mode
if self.extensions is not None:
self.matches = self._path_completions(text, state, self.extensions)
# looking for an image file
elif re.search(path_regexp,buffer):
do_shortcut = re.search('^'+'|'.join(IMG_FILE_COMMANDS),buffer)
self.matches = self._path_completions(text, state, IMG_EXTENSIONS,shortcut_ok=do_shortcut)
# looking for a seed
elif re.search('(-S\s*|--seed[=\s])\d*$',buffer):
self.matches= self._seed_completions(text,state)
add ability to import and edit alternative models online - !import_model <path/to/model/weights> will import a new model, prompt the user for its name and description, write it to the models.yaml file, and load it. - !edit_model <model_name> will bring up a previously-defined model and prompt the user to edit its descriptive fields. Example of !import_model <pre> invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b> >> Model import in process. Please enter the values needed to configure this model: Name for this model: <b>waifu-diffusion</b> Description of this model: <b>Waifu Diffusion v1.3</b> Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b> Default image width: <b>512</b> Default image height: <b>512</b> >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? <b>y</b> >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt | LatentDiffusion: Running in eps-prediction mode | DiffusionWrapper has 859.52 M params. | Making attention of type 'vanilla' with 512 in_channels | Working with z of shape (1, 4, 32, 32) = 4096 dimensions. | Making attention of type 'vanilla' with 512 in_channels | Using faster float16 precision </pre> Example of !edit_model <pre> invoke> <b>!edit_model waifu-diffusion</b> >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: <b>Waifu diffusion v1.4beta</b> weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b> config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ... </pre>
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# looking for a model
enable fast switching between models in invoke.py - This PR enables two new commands in the invoke.py script !models -- list the available models and their cache status !switch <model> -- switch to the indicated model Example: invoke> !models laion400m not loaded Latent Diffusion LAION400M model stable-diffusion-1.4 active Stable Diffusion inference model version 1.4 waifu-1.3 cached Waifu anime model version 1.3 invoke> !switch waifu-1.3 >> Caching model stable-diffusion-1.4 in system RAM >> Retrieving model waifu-1.3 from system RAM cache The name and descriptions of the models are taken from `config/models.yaml`. A future enhancement to `model_cache.py` will be to enable new model stanzas to be added to the file programmatically. This will be useful for the WebGUI. More details: - Use fast switching algorithm described in PR #948 - Models are selected using their configuration stanza name given in models.yaml. - To avoid filling up CPU RAM with cached models, this PR implements an LRU cache that monitors available CPU RAM. - The caching code allows the minimum value of available RAM to be adjusted, but invoke.py does not currently have a command-line argument that allows you to set it. The minimum free RAM is arbitrarily set to 2 GB. - Add optional description field to configs/models.yaml Unrelated fixes: - Added ">>" to CompViz model loading messages in order to make user experience more consistent. - When generating an image greater than defaults, will only warn about possible VRAM filling the first time. - Fixed bug that was causing help message to be printed twice. This involved moving the import line for the web backend into the section where it is called. Coauthored by: @ArDiouscuros
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elif re.match('^'+'|'.join(MODEL_COMMANDS),buffer):
add ability to import and edit alternative models online - !import_model <path/to/model/weights> will import a new model, prompt the user for its name and description, write it to the models.yaml file, and load it. - !edit_model <model_name> will bring up a previously-defined model and prompt the user to edit its descriptive fields. Example of !import_model <pre> invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b> >> Model import in process. Please enter the values needed to configure this model: Name for this model: <b>waifu-diffusion</b> Description of this model: <b>Waifu Diffusion v1.3</b> Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b> Default image width: <b>512</b> Default image height: <b>512</b> >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? <b>y</b> >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt | LatentDiffusion: Running in eps-prediction mode | DiffusionWrapper has 859.52 M params. | Making attention of type 'vanilla' with 512 in_channels | Working with z of shape (1, 4, 32, 32) = 4096 dimensions. | Making attention of type 'vanilla' with 512 in_channels | Using faster float16 precision </pre> Example of !edit_model <pre> invoke> <b>!edit_model waifu-diffusion</b> >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: <b>Waifu diffusion v1.4beta</b> weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b> config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ... </pre>
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self.matches= self._model_completions(text, state)
elif re.search(weight_regexp,buffer):
self.matches = self._path_completions(text, state, WEIGHT_EXTENSIONS)
enable fast switching between models in invoke.py - This PR enables two new commands in the invoke.py script !models -- list the available models and their cache status !switch <model> -- switch to the indicated model Example: invoke> !models laion400m not loaded Latent Diffusion LAION400M model stable-diffusion-1.4 active Stable Diffusion inference model version 1.4 waifu-1.3 cached Waifu anime model version 1.3 invoke> !switch waifu-1.3 >> Caching model stable-diffusion-1.4 in system RAM >> Retrieving model waifu-1.3 from system RAM cache The name and descriptions of the models are taken from `config/models.yaml`. A future enhancement to `model_cache.py` will be to enable new model stanzas to be added to the file programmatically. This will be useful for the WebGUI. More details: - Use fast switching algorithm described in PR #948 - Models are selected using their configuration stanza name given in models.yaml. - To avoid filling up CPU RAM with cached models, this PR implements an LRU cache that monitors available CPU RAM. - The caching code allows the minimum value of available RAM to be adjusted, but invoke.py does not currently have a command-line argument that allows you to set it. The minimum free RAM is arbitrarily set to 2 GB. - Add optional description field to configs/models.yaml Unrelated fixes: - Added ">>" to CompViz model loading messages in order to make user experience more consistent. - When generating an image greater than defaults, will only warn about possible VRAM filling the first time. - Fixed bug that was causing help message to be printed twice. This involved moving the import line for the web backend into the section where it is called. Coauthored by: @ArDiouscuros
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# This is the first time for this text, so build a match list.
elif text:
self.matches = [
s for s in self.options if s and s.startswith(text)
]
else:
self.matches = self.options[:]
# Return the state'th item from the match list,
# if we have that many.
try:
response = self.matches[state]
except IndexError:
response = None
return response
add ability to import and edit alternative models online - !import_model <path/to/model/weights> will import a new model, prompt the user for its name and description, write it to the models.yaml file, and load it. - !edit_model <model_name> will bring up a previously-defined model and prompt the user to edit its descriptive fields. Example of !import_model <pre> invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b> >> Model import in process. Please enter the values needed to configure this model: Name for this model: <b>waifu-diffusion</b> Description of this model: <b>Waifu Diffusion v1.3</b> Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b> Default image width: <b>512</b> Default image height: <b>512</b> >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? <b>y</b> >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt | LatentDiffusion: Running in eps-prediction mode | DiffusionWrapper has 859.52 M params. | Making attention of type 'vanilla' with 512 in_channels | Working with z of shape (1, 4, 32, 32) = 4096 dimensions. | Making attention of type 'vanilla' with 512 in_channels | Using faster float16 precision </pre> Example of !edit_model <pre> invoke> <b>!edit_model waifu-diffusion</b> >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: <b>Waifu diffusion v1.4beta</b> weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b> config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ... </pre>
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def complete_extensions(self, extensions:list):
'''
If called with a list of extensions, will force completer
to do file path completions.
'''
self.extensions=extensions
def add_history(self,line):
'''
Pass thru to readline
'''
if not self.auto_history_active:
readline.add_history(line)
def clear_history(self):
'''
Pass clear_history() thru to readline
'''
readline.clear_history()
def search_history(self,match:str):
'''
Like show_history() but only shows items that
contain the match string.
'''
self.show_history(match)
def remove_history_item(self,pos):
readline.remove_history_item(pos)
def add_seed(self, seed):
'''
Add a seed to the autocomplete list for display when -S is autocompleted.
'''
if seed is not None:
self.seeds.add(str(seed))
def set_default_dir(self, path):
self.default_dir=path
def get_line(self,index):
try:
line = self.get_history_item(index)
except IndexError:
return None
return line
def get_current_history_length(self):
return readline.get_current_history_length()
def get_history_item(self,index):
return readline.get_history_item(index)
def show_history(self,match=None):
'''
Print the session history using the pydoc pager
'''
import pydoc
lines = list()
h_len = self.get_current_history_length()
if h_len < 1:
print('<empty history>')
return
for i in range(0,h_len):
line = self.get_history_item(i+1)
if match and match not in line:
continue
lines.append(f'[{i+1}] {line}')
pydoc.pager('\n'.join(lines))
def set_line(self,line)->None:
self.linebuffer = line
readline.redisplay()
def _seed_completions(self, text, state):
m = re.search('(-S\s?|--seed[=\s]?)(\d*)',text)
if m:
switch = m.groups()[0]
partial = m.groups()[1]
else:
switch = ''
partial = text
matches = list()
for s in self.seeds:
if s.startswith(partial):
matches.append(switch+s)
matches.sort()
return matches
enable fast switching between models in invoke.py - This PR enables two new commands in the invoke.py script !models -- list the available models and their cache status !switch <model> -- switch to the indicated model Example: invoke> !models laion400m not loaded Latent Diffusion LAION400M model stable-diffusion-1.4 active Stable Diffusion inference model version 1.4 waifu-1.3 cached Waifu anime model version 1.3 invoke> !switch waifu-1.3 >> Caching model stable-diffusion-1.4 in system RAM >> Retrieving model waifu-1.3 from system RAM cache The name and descriptions of the models are taken from `config/models.yaml`. A future enhancement to `model_cache.py` will be to enable new model stanzas to be added to the file programmatically. This will be useful for the WebGUI. More details: - Use fast switching algorithm described in PR #948 - Models are selected using their configuration stanza name given in models.yaml. - To avoid filling up CPU RAM with cached models, this PR implements an LRU cache that monitors available CPU RAM. - The caching code allows the minimum value of available RAM to be adjusted, but invoke.py does not currently have a command-line argument that allows you to set it. The minimum free RAM is arbitrarily set to 2 GB. - Add optional description field to configs/models.yaml Unrelated fixes: - Added ">>" to CompViz model loading messages in order to make user experience more consistent. - When generating an image greater than defaults, will only warn about possible VRAM filling the first time. - Fixed bug that was causing help message to be printed twice. This involved moving the import line for the web backend into the section where it is called. Coauthored by: @ArDiouscuros
2022-10-12 06:14:59 +00:00
def _model_completions(self, text, state):
m = re.search('(!switch\s+)(\w*)',text)
if m:
switch = m.groups()[0]
partial = m.groups()[1]
else:
switch = ''
partial = text
matches = list()
for s in self.models:
if s.startswith(partial):
matches.append(switch+s)
matches.sort()
return matches
def _pre_input_hook(self):
if self.linebuffer:
readline.insert_text(self.linebuffer)
readline.redisplay()
self.linebuffer = None
def _path_completions(self, text, state, extensions, shortcut_ok=True):
# separate the switch from the partial path
match = re.search('^(-\w|--\w+=?)(.*)',text)
if match is None:
switch = None
partial_path = text
else:
switch,partial_path = match.groups()
partial_path = partial_path.lstrip()
matches = list()
path = os.path.expanduser(partial_path)
if os.path.isdir(path):
dir = path
elif os.path.dirname(path) != '':
dir = os.path.dirname(path)
else:
dir = ''
path= os.path.join(dir,path)
dir_list = os.listdir(dir or '.')
if shortcut_ok and os.path.exists(self.default_dir) and dir=='':
dir_list += os.listdir(self.default_dir)
for node in dir_list:
if node.startswith('.') and len(node) > 1:
continue
full_path = os.path.join(dir, node)
if not (node.endswith(extensions) or os.path.isdir(full_path)):
continue
if not full_path.startswith(path):
continue
if switch is None:
match_path = os.path.join(dir,node)
matches.append(match_path+'/' if os.path.isdir(full_path) else match_path)
elif os.path.isdir(full_path):
matches.append(
switch+os.path.join(os.path.dirname(full_path), node) + '/'
)
elif node.endswith(extensions):
matches.append(
switch+os.path.join(os.path.dirname(full_path), node)
)
return matches
class DummyCompleter(Completer):
def __init__(self,options):
super().__init__(options)
self.history = list()
def add_history(self,line):
self.history.append(line)
def clear_history(self):
self.history = list()
def get_current_history_length(self):
return len(self.history)
def get_history_item(self,index):
return self.history[index-1]
def remove_history_item(self,index):
return self.history.pop(index-1)
def set_line(self,line):
print(f'# {line}')
enable fast switching between models in invoke.py - This PR enables two new commands in the invoke.py script !models -- list the available models and their cache status !switch <model> -- switch to the indicated model Example: invoke> !models laion400m not loaded Latent Diffusion LAION400M model stable-diffusion-1.4 active Stable Diffusion inference model version 1.4 waifu-1.3 cached Waifu anime model version 1.3 invoke> !switch waifu-1.3 >> Caching model stable-diffusion-1.4 in system RAM >> Retrieving model waifu-1.3 from system RAM cache The name and descriptions of the models are taken from `config/models.yaml`. A future enhancement to `model_cache.py` will be to enable new model stanzas to be added to the file programmatically. This will be useful for the WebGUI. More details: - Use fast switching algorithm described in PR #948 - Models are selected using their configuration stanza name given in models.yaml. - To avoid filling up CPU RAM with cached models, this PR implements an LRU cache that monitors available CPU RAM. - The caching code allows the minimum value of available RAM to be adjusted, but invoke.py does not currently have a command-line argument that allows you to set it. The minimum free RAM is arbitrarily set to 2 GB. - Add optional description field to configs/models.yaml Unrelated fixes: - Added ">>" to CompViz model loading messages in order to make user experience more consistent. - When generating an image greater than defaults, will only warn about possible VRAM filling the first time. - Fixed bug that was causing help message to be printed twice. This involved moving the import line for the web backend into the section where it is called. Coauthored by: @ArDiouscuros
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def get_completer(opt:Args, models=[])->Completer:
if readline_available:
enable fast switching between models in invoke.py - This PR enables two new commands in the invoke.py script !models -- list the available models and their cache status !switch <model> -- switch to the indicated model Example: invoke> !models laion400m not loaded Latent Diffusion LAION400M model stable-diffusion-1.4 active Stable Diffusion inference model version 1.4 waifu-1.3 cached Waifu anime model version 1.3 invoke> !switch waifu-1.3 >> Caching model stable-diffusion-1.4 in system RAM >> Retrieving model waifu-1.3 from system RAM cache The name and descriptions of the models are taken from `config/models.yaml`. A future enhancement to `model_cache.py` will be to enable new model stanzas to be added to the file programmatically. This will be useful for the WebGUI. More details: - Use fast switching algorithm described in PR #948 - Models are selected using their configuration stanza name given in models.yaml. - To avoid filling up CPU RAM with cached models, this PR implements an LRU cache that monitors available CPU RAM. - The caching code allows the minimum value of available RAM to be adjusted, but invoke.py does not currently have a command-line argument that allows you to set it. The minimum free RAM is arbitrarily set to 2 GB. - Add optional description field to configs/models.yaml Unrelated fixes: - Added ">>" to CompViz model loading messages in order to make user experience more consistent. - When generating an image greater than defaults, will only warn about possible VRAM filling the first time. - Fixed bug that was causing help message to be printed twice. This involved moving the import line for the web backend into the section where it is called. Coauthored by: @ArDiouscuros
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completer = Completer(COMMANDS,models)
readline.set_completer(
completer.complete
)
# pyreadline3 does not have a set_auto_history() method
try:
readline.set_auto_history(False)
completer.auto_history_active = False
except:
completer.auto_history_active = True
readline.set_pre_input_hook(completer._pre_input_hook)
readline.set_completer_delims(' ')
readline.parse_and_bind('tab: complete')
readline.parse_and_bind('set print-completions-horizontally off')
readline.parse_and_bind('set page-completions on')
readline.parse_and_bind('set skip-completed-text on')
readline.parse_and_bind('set show-all-if-ambiguous on')
histfile = os.path.join(os.path.expanduser(opt.outdir), '.invoke_history')
try:
readline.read_history_file(histfile)
readline.set_history_length(1000)
except FileNotFoundError:
pass
atexit.register(readline.write_history_file, histfile)
else:
completer = DummyCompleter(COMMANDS)
return completer